Adapters
Safetensors
English
llama
4-bit precision
bitsandbytes
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  ---
 
 
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  license: mit
 
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  datasets:
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  - argilla/distilabel-intel-orca-dpo-pairs
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  - jondurbin/truthy-dpo-v0.1
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  - argilla/distilabel-math-preference-dpo
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  - argilla/distilabel-capybara-dpo-7k-binarized
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- language:
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- - en
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- library_name: adapter-transformers
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  base_model: Technoculture/MT7Bi-sft
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Technoculture/MedMerge-6-7b-alpha-dpo
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  ### For full details of this dpo-training please read our notebook.
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  <a target="_blank" href="https://colab.research.google.com/github/dkshjn/Technoculture/blob/main/MedMerge_6_7b_alpha_dpo.ipynb">
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  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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- </a>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - en
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  license: mit
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+ library_name: adapter-transformers
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  datasets:
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  - argilla/distilabel-intel-orca-dpo-pairs
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  - jondurbin/truthy-dpo-v0.1
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  - argilla/distilabel-math-preference-dpo
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  - argilla/distilabel-capybara-dpo-7k-binarized
 
 
 
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  base_model: Technoculture/MT7Bi-sft
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+ model-index:
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+ - name: MedMerge-6-7b-alpha-dpo
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: AI2 Reasoning Challenge (25-Shot)
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+ type: ai2_arc
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+ config: ARC-Challenge
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+ split: test
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+ args:
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+ num_few_shot: 25
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+ metrics:
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+ - type: acc_norm
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+ value: 54.27
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: HellaSwag (10-Shot)
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+ type: hellaswag
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+ split: validation
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+ args:
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+ num_few_shot: 10
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+ metrics:
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+ - type: acc_norm
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+ value: 75.6
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU (5-Shot)
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+ type: cais/mmlu
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+ config: all
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 52.65
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: TruthfulQA (0-shot)
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+ type: truthful_qa
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+ config: multiple_choice
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+ split: validation
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: mc2
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+ value: 43.94
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: Winogrande (5-shot)
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+ type: winogrande
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+ config: winogrande_xl
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+ split: validation
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 71.03
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GSM8k (5-shot)
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+ type: gsm8k
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 26.16
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Technoculture/MedMerge-6-7b-alpha-dpo
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+ name: Open LLM Leaderboard
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  ---
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  # Technoculture/MedMerge-6-7b-alpha-dpo
 
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  ### For full details of this dpo-training please read our notebook.
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  <a target="_blank" href="https://colab.research.google.com/github/dkshjn/Technoculture/blob/main/MedMerge_6_7b_alpha_dpo.ipynb">
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  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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+ </a>
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MedMerge-6-7b-alpha-dpo)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |53.94|
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+ |AI2 Reasoning Challenge (25-Shot)|54.27|
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+ |HellaSwag (10-Shot) |75.60|
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+ |MMLU (5-Shot) |52.65|
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+ |TruthfulQA (0-shot) |43.94|
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+ |Winogrande (5-shot) |71.03|
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+ |GSM8k (5-shot) |26.16|
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+